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<h1 id="sec_name">
<span data-if="hdevelop" style="display:inline;">get_deep_ocr_param</span><span data-if="c" style="display:none;">T_get_deep_ocr_param</span><span data-if="cpp" style="display:none;">GetDeepOcrParam</span><span data-if="dotnet" style="display:none;">GetDeepOcrParam</span><span data-if="python" style="display:none;">get_deep_ocr_param</span> (算子名称)</h1>
<h2>名称</h2>
<p><code><span data-if="hdevelop" style="display:inline;">get_deep_ocr_param</span><span data-if="c" style="display:none;">T_get_deep_ocr_param</span><span data-if="cpp" style="display:none;">GetDeepOcrParam</span><span data-if="dotnet" style="display:none;">GetDeepOcrParam</span><span data-if="python" style="display:none;">get_deep_ocr_param</span></code> — Return the parameters of a Deep OCR model.</p>
<h2 id="sec_synopsis">参数签名</h2>
<div data-if="hdevelop" style="display:inline;">
<p>
<code><b>get_deep_ocr_param</b>( :  : <a href="#DeepOcrHandle"><i>DeepOcrHandle</i></a>, <a href="#GenParamName"><i>GenParamName</i></a> : <a href="#GenParamValue"><i>GenParamValue</i></a>)</code></p>
</div>
<div data-if="c" style="display:none;">
<p>
<code>Herror <b>T_get_deep_ocr_param</b>(const Htuple <a href="#DeepOcrHandle"><i>DeepOcrHandle</i></a>, const Htuple <a href="#GenParamName"><i>GenParamName</i></a>, Htuple* <a href="#GenParamValue"><i>GenParamValue</i></a>)</code></p>
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<p>
<code>void <b>GetDeepOcrParam</b>(const HTuple&amp; <a href="#DeepOcrHandle"><i>DeepOcrHandle</i></a>, const HTuple&amp; <a href="#GenParamName"><i>GenParamName</i></a>, HTuple* <a href="#GenParamValue"><i>GenParamValue</i></a>)</code></p>
<p>
<code><a href="HTuple.html">HTuple</a> <a href="HDlModelOcr.html">HDlModelOcr</a>::<b>GetDeepOcrParam</b>(const HString&amp; <a href="#GenParamName"><i>GenParamName</i></a>) const</code></p>
<p>
<code><a href="HTuple.html">HTuple</a> <a href="HDlModelOcr.html">HDlModelOcr</a>::<b>GetDeepOcrParam</b>(const char* <a href="#GenParamName"><i>GenParamName</i></a>) const</code></p>
<p>
<code><a href="HTuple.html">HTuple</a> <a href="HDlModelOcr.html">HDlModelOcr</a>::<b>GetDeepOcrParam</b>(const wchar_t* <a href="#GenParamName"><i>GenParamName</i></a>) const  <span class="signnote">
            (
            Windows only)
          </span></code></p>
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<code>static void <a href="HOperatorSet.html">HOperatorSet</a>.<b>GetDeepOcrParam</b>(<a href="HTuple.html">HTuple</a> <a href="#DeepOcrHandle"><i>deepOcrHandle</i></a>, <a href="HTuple.html">HTuple</a> <a href="#GenParamName"><i>genParamName</i></a>, out <a href="HTuple.html">HTuple</a> <a href="#GenParamValue"><i>genParamValue</i></a>)</code></p>
<p>
<code><a href="HTuple.html">HTuple</a> <a href="HDlModelOcr.html">HDlModelOcr</a>.<b>GetDeepOcrParam</b>(string <a href="#GenParamName"><i>genParamName</i></a>)</code></p>
</div>
<div data-if="python" style="display:none;">
<p>
<code>def <b>get_deep_ocr_param</b>(<a href="#DeepOcrHandle"><i>deep_ocr_handle</i></a>: HHandle, <a href="#GenParamName"><i>gen_param_name</i></a>: str) -&gt; Sequence[HTupleElementType]</code></p>
<p>
<code>def <b>get_deep_ocr_param_s</b>(<a href="#DeepOcrHandle"><i>deep_ocr_handle</i></a>: HHandle, <a href="#GenParamName"><i>gen_param_name</i></a>: str) -&gt; HTupleElementType</code></p>
</div>
<h2 id="sec_description">描述</h2>
<p><code><span data-if="hdevelop" style="display:inline">get_deep_ocr_param</span><span data-if="c" style="display:none">get_deep_ocr_param</span><span data-if="cpp" style="display:none">GetDeepOcrParam</span><span data-if="com" style="display:none">GetDeepOcrParam</span><span data-if="dotnet" style="display:none">GetDeepOcrParam</span><span data-if="python" style="display:none">get_deep_ocr_param</span></code> returns the parameter values
<a href="#GenParamValue"><i><code><span data-if="hdevelop" style="display:inline">GenParamValue</span><span data-if="c" style="display:none">GenParamValue</span><span data-if="cpp" style="display:none">GenParamValue</span><span data-if="com" style="display:none">GenParamValue</span><span data-if="dotnet" style="display:none">genParamValue</span><span data-if="python" style="display:none">gen_param_value</span></code></i></a> of <a href="#GenParamName"><i><code><span data-if="hdevelop" style="display:inline">GenParamName</span><span data-if="c" style="display:none">GenParamName</span><span data-if="cpp" style="display:none">GenParamName</span><span data-if="com" style="display:none">GenParamName</span><span data-if="dotnet" style="display:none">genParamName</span><span data-if="python" style="display:none">gen_param_name</span></code></i></a> for the Deep OCR model
<a href="#DeepOcrHandle"><i><code><span data-if="hdevelop" style="display:inline">DeepOcrHandle</span><span data-if="c" style="display:none">DeepOcrHandle</span><span data-if="cpp" style="display:none">DeepOcrHandle</span><span data-if="com" style="display:none">DeepOcrHandle</span><span data-if="dotnet" style="display:none">deepOcrHandle</span><span data-if="python" style="display:none">deep_ocr_handle</span></code></i></a>.
</p>
<p>Parameters can apply to the whole model or be specific for a given component.
The following table gives an overview, which parameters can be set and
which ones retrieved as well as for which model part they apply.
</p>
<div style="text-align:center"><table style="width:85%;margin-left:auto;margin-right:auto" class="table">
<col span="1" style="width:40%;">
<col span="1" style="width:15%;">
<col span="1" style="width:15%;">
<col span="1" style="width:15%;">
<tr>
<th style="text-align:left">
<a href="#GenParamName"><i><code><span data-if="hdevelop" style="display:inline">GenParamName</span><span data-if="c" style="display:none">GenParamName</span><span data-if="cpp" style="display:none">GenParamName</span><span data-if="com" style="display:none">GenParamName</span><span data-if="dotnet" style="display:none">genParamName</span><span data-if="python" style="display:none">gen_param_name</span></code></i></a>                          </th>
<th style="text-align:left">Model                   </th>
<th style="text-align:left">Det. comp.              </th>
<th style="text-align:left">Recog. comp.</th>
</tr>
<tr>
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<i><span data-if="hdevelop" style="display:inline">'device'</span><span data-if="c" style="display:none">"device"</span><span data-if="cpp" style="display:none">"device"</span><span data-if="com" style="display:none">"device"</span><span data-if="dotnet" style="display:none">"device"</span><span data-if="python" style="display:none">"device"</span></i>                              </td>
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<i><span data-if="hdevelop" style="display:inline">'detection_min_link_score'</span><span data-if="c" style="display:none">"detection_min_link_score"</span><span data-if="cpp" style="display:none">"detection_min_link_score"</span><span data-if="com" style="display:none">"detection_min_link_score"</span><span data-if="dotnet" style="display:none">"detection_min_link_score"</span><span data-if="python" style="display:none">"detection_min_link_score"</span></i>            </td>
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<i><span data-if="hdevelop" style="display:inline">'detection_min_word_area'</span><span data-if="c" style="display:none">"detection_min_word_area"</span><span data-if="cpp" style="display:none">"detection_min_word_area"</span><span data-if="com" style="display:none">"detection_min_word_area"</span><span data-if="dotnet" style="display:none">"detection_min_word_area"</span><span data-if="python" style="display:none">"detection_min_word_area"</span></i>             </td>
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<td style="text-align:left">
<i><span data-if="hdevelop" style="display:inline">'detection_min_word_score'</span><span data-if="c" style="display:none">"detection_min_word_score"</span><span data-if="cpp" style="display:none">"detection_min_word_score"</span><span data-if="com" style="display:none">"detection_min_word_score"</span><span data-if="dotnet" style="display:none">"detection_min_word_score"</span><span data-if="python" style="display:none">"detection_min_word_score"</span></i>            </td>
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<i><span data-if="hdevelop" style="display:inline">'detection_model'</span><span data-if="c" style="display:none">"detection_model"</span><span data-if="cpp" style="display:none">"detection_model"</span><span data-if="com" style="display:none">"detection_model"</span><span data-if="dotnet" style="display:none">"detection_model"</span><span data-if="python" style="display:none">"detection_model"</span></i>                     </td>
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<i><span data-if="hdevelop" style="display:inline">'detection_tiling'</span><span data-if="c" style="display:none">"detection_tiling"</span><span data-if="cpp" style="display:none">"detection_tiling"</span><span data-if="com" style="display:none">"detection_tiling"</span><span data-if="dotnet" style="display:none">"detection_tiling"</span><span data-if="python" style="display:none">"detection_tiling"</span></i>                    </td>
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<i><span data-if="hdevelop" style="display:inline">'recognition_alphabet_internal'</span><span data-if="c" style="display:none">"recognition_alphabet_internal"</span><span data-if="cpp" style="display:none">"recognition_alphabet_internal"</span><span data-if="com" style="display:none">"recognition_alphabet_internal"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_internal"</span><span data-if="python" style="display:none">"recognition_alphabet_internal"</span></i>       </td>
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<i><span data-if="hdevelop" style="display:inline">'recognition_batch_size'</span><span data-if="c" style="display:none">"recognition_batch_size"</span><span data-if="cpp" style="display:none">"recognition_batch_size"</span><span data-if="com" style="display:none">"recognition_batch_size"</span><span data-if="dotnet" style="display:none">"recognition_batch_size"</span><span data-if="python" style="display:none">"recognition_batch_size"</span></i>              </td>
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<i><span data-if="hdevelop" style="display:inline">'recognition_device'</span><span data-if="c" style="display:none">"recognition_device"</span><span data-if="cpp" style="display:none">"recognition_device"</span><span data-if="com" style="display:none">"recognition_device"</span><span data-if="dotnet" style="display:none">"recognition_device"</span><span data-if="python" style="display:none">"recognition_device"</span></i>                  </td>
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<i><span data-if="hdevelop" style="display:inline">'recognition_image_dimensions'</span><span data-if="c" style="display:none">"recognition_image_dimensions"</span><span data-if="cpp" style="display:none">"recognition_image_dimensions"</span><span data-if="com" style="display:none">"recognition_image_dimensions"</span><span data-if="dotnet" style="display:none">"recognition_image_dimensions"</span><span data-if="python" style="display:none">"recognition_image_dimensions"</span></i>        </td>
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<i><span data-if="hdevelop" style="display:inline">'recognition_image_height'</span><span data-if="c" style="display:none">"recognition_image_height"</span><span data-if="cpp" style="display:none">"recognition_image_height"</span><span data-if="com" style="display:none">"recognition_image_height"</span><span data-if="dotnet" style="display:none">"recognition_image_height"</span><span data-if="python" style="display:none">"recognition_image_height"</span></i>            </td>
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<tr>
<td style="text-align:left">
<i><span data-if="hdevelop" style="display:inline">'recognition_image_width'</span><span data-if="c" style="display:none">"recognition_image_width"</span><span data-if="cpp" style="display:none">"recognition_image_width"</span><span data-if="com" style="display:none">"recognition_image_width"</span><span data-if="dotnet" style="display:none">"recognition_image_width"</span><span data-if="python" style="display:none">"recognition_image_width"</span></i>             </td>
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<td style="text-align:left">
<i><span data-if="hdevelop" style="display:inline">'recognition_model'</span><span data-if="c" style="display:none">"recognition_model"</span><span data-if="cpp" style="display:none">"recognition_model"</span><span data-if="com" style="display:none">"recognition_model"</span><span data-if="dotnet" style="display:none">"recognition_model"</span><span data-if="python" style="display:none">"recognition_model"</span></i>                   </td>
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<i><span data-if="hdevelop" style="display:inline">'recognition_num_char_candidates'</span><span data-if="c" style="display:none">"recognition_num_char_candidates"</span><span data-if="cpp" style="display:none">"recognition_num_char_candidates"</span><span data-if="com" style="display:none">"recognition_num_char_candidates"</span><span data-if="dotnet" style="display:none">"recognition_num_char_candidates"</span><span data-if="python" style="display:none">"recognition_num_char_candidates"</span></i>     </td>
<td style="text-align:left">
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<tr><td style="text-align:left">
</td></tr>
</table></div>
Thereby, the symbols and abbreviations denote the following :
<ul>
<li>
<p> 's': The parameter can be set using <a href="set_deep_ocr_param.html"><code><span data-if="hdevelop" style="display:inline">set_deep_ocr_param</span><span data-if="c" style="display:none">set_deep_ocr_param</span><span data-if="cpp" style="display:none">SetDeepOcrParam</span><span data-if="com" style="display:none">SetDeepOcrParam</span><span data-if="dotnet" style="display:none">SetDeepOcrParam</span><span data-if="python" style="display:none">set_deep_ocr_param</span></code></a>.
</p>
</li>
<li>
<p> 'g': The parameter can be retrieved using <code><span data-if="hdevelop" style="display:inline">get_deep_ocr_param</span><span data-if="c" style="display:none">get_deep_ocr_param</span><span data-if="cpp" style="display:none">GetDeepOcrParam</span><span data-if="com" style="display:none">GetDeepOcrParam</span><span data-if="dotnet" style="display:none">GetDeepOcrParam</span><span data-if="python" style="display:none">get_deep_ocr_param</span></code>.
</p>
</li>
<li>
<p> '-': The parameter is not applicable.
</p>
</li>
<li>
<p> Model: Entire Deep OCR model with all its components.
</p>
</li>
<li>
<p> Det. comp.: Detection component.
</p>
</li>
<li>
<p> Recog. comp.: Recognition component.
</p>
</li>
</ul>
<p>Only parameters that do not change the model architecture can be set after
the model has been optimized with <a href="optimize_dl_model_for_inference.html"><code><span data-if="hdevelop" style="display:inline">optimize_dl_model_for_inference</span><span data-if="c" style="display:none">optimize_dl_model_for_inference</span><span data-if="cpp" style="display:none">OptimizeDlModelForInference</span><span data-if="com" style="display:none">OptimizeDlModelForInference</span><span data-if="dotnet" style="display:none">OptimizeDlModelForInference</span><span data-if="python" style="display:none">optimize_dl_model_for_inference</span></code></a>.
A list of these parameters can be found at
<a href="optimize_dl_model_for_inference.html"><code><span data-if="hdevelop" style="display:inline">optimize_dl_model_for_inference</span><span data-if="c" style="display:none">optimize_dl_model_for_inference</span><span data-if="cpp" style="display:none">OptimizeDlModelForInference</span><span data-if="com" style="display:none">OptimizeDlModelForInference</span><span data-if="dotnet" style="display:none">OptimizeDlModelForInference</span><span data-if="python" style="display:none">optimize_dl_model_for_inference</span></code></a>.
In the following the parameters are described, sorted according to the part
of the model they apply to:
</p>
<dl class="generic">

<dt><b>Entire model:</b></dt>
<dd>
<p>

</p>
<dl class="generic">

<dt><b><i><span data-if="hdevelop" style="display:inline">'device'</span><span data-if="c" style="display:none">"device"</span><span data-if="cpp" style="display:none">"device"</span><span data-if="com" style="display:none">"device"</span><span data-if="dotnet" style="display:none">"device"</span><span data-if="python" style="display:none">"device"</span></i>:</b></dt>
<dd>
<p>

Handle of the device on which the model will be executed.
To get a tuple of handles of all available potentially Deep-OCR-capable
compute devices use <a href="query_available_dl_devices.html"><code><span data-if="hdevelop" style="display:inline">query_available_dl_devices</span><span data-if="c" style="display:none">query_available_dl_devices</span><span data-if="cpp" style="display:none">QueryAvailableDlDevices</span><span data-if="com" style="display:none">QueryAvailableDlDevices</span><span data-if="dotnet" style="display:none">QueryAvailableDlDevices</span><span data-if="python" style="display:none">query_available_dl_devices</span></code></a>.</p>
<p>
Note, the device can be reset for an individual component, in which case
only the possibly remaining part of the model (e.g., the remaining
component) will be executed on the device of this handle.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> Handle of the default device, thus the GPU with index
<i>0</i> when querying a list using <a href="get_system.html"><code><span data-if="hdevelop" style="display:inline">get_system</span><span data-if="c" style="display:none">get_system</span><span data-if="cpp" style="display:none">GetSystem</span><span data-if="com" style="display:none">GetSystem</span><span data-if="dotnet" style="display:none">GetSystem</span><span data-if="python" style="display:none">get_system</span></code></a>
with <i><span data-if="hdevelop" style="display:inline">'cuda_devices'</span><span data-if="c" style="display:none">"cuda_devices"</span><span data-if="cpp" style="display:none">"cuda_devices"</span><span data-if="com" style="display:none">"cuda_devices"</span><span data-if="dotnet" style="display:none">"cuda_devices"</span><span data-if="python" style="display:none">"cuda_devices"</span></i>.
If no device is available, this is an empty tuple.
</p>
</dd>
</dl>

</dd>

<dt><b>Detection component:</b></dt>
<dd>
<p>

</p>
<dl class="generic">

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_device'</span><span data-if="c" style="display:none">"detection_device"</span><span data-if="cpp" style="display:none">"detection_device"</span><span data-if="com" style="display:none">"detection_device"</span><span data-if="dotnet" style="display:none">"detection_device"</span><span data-if="python" style="display:none">"detection_device"</span></i>:</b></dt>
<dd>
<p>

This parameter will set the device on which the detection component of
the Deep OCR model is executed. For a further description, see
<i><span data-if="hdevelop" style="display:inline">'device'</span><span data-if="c" style="display:none">"device"</span><span data-if="cpp" style="display:none">"device"</span><span data-if="com" style="display:none">"device"</span><span data-if="dotnet" style="display:none">"device"</span><span data-if="python" style="display:none">"device"</span></i>.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> The same value as for <i><span data-if="hdevelop" style="display:inline">'device'</span><span data-if="c" style="display:none">"device"</span><span data-if="cpp" style="display:none">"device"</span><span data-if="com" style="display:none">"device"</span><span data-if="dotnet" style="display:none">"device"</span><span data-if="python" style="display:none">"device"</span></i>.
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_image_dimensions'</span><span data-if="c" style="display:none">"detection_image_dimensions"</span><span data-if="cpp" style="display:none">"detection_image_dimensions"</span><span data-if="com" style="display:none">"detection_image_dimensions"</span><span data-if="dotnet" style="display:none">"detection_image_dimensions"</span><span data-if="python" style="display:none">"detection_image_dimensions"</span></i>:</b></dt>
<dd>
<p>

Tuple containing the image dimensions (<i><span data-if="hdevelop" style="display:inline">'detection_image_width'</span><span data-if="c" style="display:none">"detection_image_width"</span><span data-if="cpp" style="display:none">"detection_image_width"</span><span data-if="com" style="display:none">"detection_image_width"</span><span data-if="dotnet" style="display:none">"detection_image_width"</span><span data-if="python" style="display:none">"detection_image_width"</span></i>,
<i><span data-if="hdevelop" style="display:inline">'detection_image_height'</span><span data-if="c" style="display:none">"detection_image_height"</span><span data-if="cpp" style="display:none">"detection_image_height"</span><span data-if="com" style="display:none">"detection_image_height"</span><span data-if="dotnet" style="display:none">"detection_image_height"</span><span data-if="python" style="display:none">"detection_image_height"</span></i>, number of channels) the detection
component will process.</p>
<p>
The input image is scaled to <i><span data-if="hdevelop" style="display:inline">'detection_image_dimensions'</span><span data-if="c" style="display:none">"detection_image_dimensions"</span><span data-if="cpp" style="display:none">"detection_image_dimensions"</span><span data-if="com" style="display:none">"detection_image_dimensions"</span><span data-if="dotnet" style="display:none">"detection_image_dimensions"</span><span data-if="python" style="display:none">"detection_image_dimensions"</span></i>
such that the original aspect ratio is preserved. The scaled image
is padded with gray value <i>0</i> if necessary. Therefore, changing
the <i><span data-if="hdevelop" style="display:inline">'detection_image_height'</span><span data-if="c" style="display:none">"detection_image_height"</span><span data-if="cpp" style="display:none">"detection_image_height"</span><span data-if="com" style="display:none">"detection_image_height"</span><span data-if="dotnet" style="display:none">"detection_image_height"</span><span data-if="python" style="display:none">"detection_image_height"</span></i> or <i><span data-if="hdevelop" style="display:inline">'detection_image_width'</span><span data-if="c" style="display:none">"detection_image_width"</span><span data-if="cpp" style="display:none">"detection_image_width"</span><span data-if="com" style="display:none">"detection_image_width"</span><span data-if="dotnet" style="display:none">"detection_image_width"</span><span data-if="python" style="display:none">"detection_image_width"</span></i>
can influence the results.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> [<i>1024</i>, <i>1024</i>, <i>3</i>]
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_image_height'</span><span data-if="c" style="display:none">"detection_image_height"</span><span data-if="cpp" style="display:none">"detection_image_height"</span><span data-if="com" style="display:none">"detection_image_height"</span><span data-if="dotnet" style="display:none">"detection_image_height"</span><span data-if="python" style="display:none">"detection_image_height"</span></i>:</b></dt>
<dd>
<p>

Height of the images the detection component will process.
This means, the network preserves the aspect ratio of the input image by
scaling it to a maximum of this height before processing it. Thus this size
can influence the results.</p>
<p>
The model architecture requires that the height is a multiple of 32. If
this is not the case, the height is rounded up to the nearest integer
multiple of 32.</p>
<p>
<span class="pardesc"><span class="parcat">Suggested values:
      </span></span> <i>768</i>, <i>1024</i>, <i>1280</i></p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i>1024</i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_image_size'</span><span data-if="c" style="display:none">"detection_image_size"</span><span data-if="cpp" style="display:none">"detection_image_size"</span><span data-if="com" style="display:none">"detection_image_size"</span><span data-if="dotnet" style="display:none">"detection_image_size"</span><span data-if="python" style="display:none">"detection_image_size"</span></i>:</b></dt>
<dd>
<p>

Tuple containing the image size (<i><span data-if="hdevelop" style="display:inline">'detection_image_width'</span><span data-if="c" style="display:none">"detection_image_width"</span><span data-if="cpp" style="display:none">"detection_image_width"</span><span data-if="com" style="display:none">"detection_image_width"</span><span data-if="dotnet" style="display:none">"detection_image_width"</span><span data-if="python" style="display:none">"detection_image_width"</span></i>,
<i><span data-if="hdevelop" style="display:inline">'detection_image_height'</span><span data-if="c" style="display:none">"detection_image_height"</span><span data-if="cpp" style="display:none">"detection_image_height"</span><span data-if="com" style="display:none">"detection_image_height"</span><span data-if="dotnet" style="display:none">"detection_image_height"</span><span data-if="python" style="display:none">"detection_image_height"</span></i>) the detection component will
process.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> [<i>1024</i>, <i>1024</i>]
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_image_width'</span><span data-if="c" style="display:none">"detection_image_width"</span><span data-if="cpp" style="display:none">"detection_image_width"</span><span data-if="com" style="display:none">"detection_image_width"</span><span data-if="dotnet" style="display:none">"detection_image_width"</span><span data-if="python" style="display:none">"detection_image_width"</span></i>:</b></dt>
<dd>
<p>

Width of the images the detection component will process.
This means, the network preserves the aspect ratio of the input image by
scaling it to a maximum of this width before processing it. Thus this size
can influence the results.</p>
<p>
The model architecture requires that the width is a multiple of 32. If
this is not the case, the width is rounded up to the nearest integer
multiple of 32.</p>
<p>
<span class="pardesc"><span class="parcat">Suggested values:
      </span></span> <i>768</i>, <i>1024</i>, <i>1280</i></p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i>1024</i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_min_character_score'</span><span data-if="c" style="display:none">"detection_min_character_score"</span><span data-if="cpp" style="display:none">"detection_min_character_score"</span><span data-if="com" style="display:none">"detection_min_character_score"</span><span data-if="dotnet" style="display:none">"detection_min_character_score"</span><span data-if="python" style="display:none">"detection_min_character_score"</span></i>:</b></dt>
<dd>
<p>

The parameter <i><span data-if="hdevelop" style="display:inline">'detection_min_character_score'</span><span data-if="c" style="display:none">"detection_min_character_score"</span><span data-if="cpp" style="display:none">"detection_min_character_score"</span><span data-if="com" style="display:none">"detection_min_character_score"</span><span data-if="dotnet" style="display:none">"detection_min_character_score"</span><span data-if="python" style="display:none">"detection_min_character_score"</span></i> specifies the lower
threshold used for the character score map to estimate the dimensions of
the characters.
By adjusting the parameter, suggested instances can be split up or
neighboring instances can be merged.</p>
<p>
<span class="pardesc"><span class="parcat">Value range:
      </span></span> <span title="76" style="vertical-align:-0.37221em" class="math"><!-- Created by MetaPost 1.902 on 2023.05.15:2033 --><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" version="1.1" width="3.35168em" height="1.12127em" viewBox="0 0 53.626907 17.940399">
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    </g>
    <g transform="scale(0.009963,0.009963)" id="GLYPHcmr10_93">
      <path style="fill-rule: evenodd;" d="M159.000000 -750.000000L22.000000 -750.000000L22.000000 -710.000000L119.000000 -710.000000L119.000000 210.000000L22.000000 210.000000L22.000000 250.000000L159.000000 250.000000"></path>
    </g>
    <g transform="scale(0.009963,0.009963)" id="GLYPHcmsy10_50">
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    </g>
    <g transform="scale(0.009963,0.009963)" id="GLYPHcmmi10_59">
      <path style="fill-rule: evenodd;" d="M203.000000 -1.000000C203.000000 -67.000000,178.000000 -106.000000,139.000000 -106.000000C106.000000 -106.000000,86.000000 -81.000000,86.000000 -53.000000C86.000000 -26.000000,106.000000 -0.000000,139.000000 -0.000000C151.000000 -0.000000,164.000000 -4.000000,174.000000 -13.000000C177.000000 -15.000000,178.000000 -16.000000,179.000000 -16.000000C180.000000 -16.000000,181.000000 -15.000000,181.000000 -1.000000C181.000000 73.000000,146.000000 133.000000,113.000000 166.000000C102.000000 177.000000,102.000000 179.000000,102.000000 182.000000C102.000000 189.000000,107.000000 193.000000,112.000000 193.000000C123.000000 193.000000,203.000000 116.000000,203.000000 -1.000000"></path>
    </g>
    <g transform="scale(0.009963,0.009963)" id="GLYPHcmti10_48">
      <path style="fill-rule: evenodd;" d="M555.000000 -496.000000C555.000000 -536.000000,550.000000 -666.000000,421.000000 -666.000000C349.000000 -666.000000,269.000000 -619.000000,209.000000 -505.000000C160.000000 -412.000000,117.000000 -237.000000,117.000000 -148.000000C117.000000 -117.000000,117.000000 22.000000,251.000000 22.000000C317.000000 22.000000,411.000000 -19.000000,476.000000 -164.000000C517.000000 -257.000000,555.000000 -415.000000,555.000000 -496.000000M256.000000 -0.000000C224.000000 -0.000000,181.000000 -20.000000,181.000000 -98.000000C181.000000 -180.000000,256.000000 -475.000000,291.000000 -547.000000C328.000000 -622.000000,382.000000 -644.000000,416.000000 -644.000000C457.000000 -644.000000,493.000000 -614.000000,493.000000 -550.000000C493.000000 -476.000000,423.000000 -193.000000,380.000000 -98.000000C358.000000 -51.000000,308.000000 -0.000000,256.000000 -0.000000"></path>
    </g>
    <g transform="scale(0.009963,0.009963)" id="GLYPHcmti10_49">
      <path style="fill-rule: evenodd;" d="M458.000000 -641.000000C459.000000 -644.000000,461.000000 -652.000000,461.000000 -654.000000C461.000000 -662.000000,455.000000 -666.000000,449.000000 -666.000000C443.000000 -666.000000,442.000000 -665.000000,430.000000 -650.000000C353.000000 -547.000000,283.000000 -540.000000,254.000000 -537.000000C249.000000 -536.000000,238.000000 -535.000000,238.000000 -518.000000C238.000000 -506.000000,250.000000 -506.000000,254.000000 -506.000000C269.000000 -506.000000,318.000000 -512.000000,365.000000 -547.000000L247.000000 -73.000000C239.000000 -41.000000,231.000000 -31.000000,153.000000 -31.000000L145.000000 -31.000000C128.000000 -31.000000,117.000000 -31.000000,117.000000 -12.000000C117.000000 -0.000000,128.000000 -0.000000,132.000000 -0.000000L263.000000 -0.000000L175.000000 -0.000000L220.000000 -3.000000L263.000000 -3.000000L307.000000 -3.000000L353.000000 -0.000000L397.000000 -0.000000C404.000000 -0.000000,417.000000 -0.000000,417.000000 -19.000000C417.000000 -31.000000,407.000000 -31.000000,391.000000 -31.000000L383.000000 -31.000000C370.000000 -31.000000,353.000000 -32.000000,340.000000 -33.000000C318.000000 -36.000000,312.000000 -37.000000,312.000000 -51.000000C312.000000 -57.000000,314.000000 -66.000000,315.000000 -70.000000"></path>
    </g>
  </defs>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,0.202530 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmsy10_50"></use>
  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,15.257156 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmr10_91"></use>
  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,19.684998 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmti10_48"></use>
  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,29.993042 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmmi10_59"></use>
  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,37.077545 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmti10_49"></use>
  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,47.385590 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmr10_93"></use>
  </g>
</svg></span>.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i>0.5</i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_min_link_score'</span><span data-if="c" style="display:none">"detection_min_link_score"</span><span data-if="cpp" style="display:none">"detection_min_link_score"</span><span data-if="com" style="display:none">"detection_min_link_score"</span><span data-if="dotnet" style="display:none">"detection_min_link_score"</span><span data-if="python" style="display:none">"detection_min_link_score"</span></i>:</b></dt>
<dd>
<p>

The parameter <i><span data-if="hdevelop" style="display:inline">'detection_min_link_score'</span><span data-if="c" style="display:none">"detection_min_link_score"</span><span data-if="cpp" style="display:none">"detection_min_link_score"</span><span data-if="com" style="display:none">"detection_min_link_score"</span><span data-if="dotnet" style="display:none">"detection_min_link_score"</span><span data-if="python" style="display:none">"detection_min_link_score"</span></i> defines the minimum link
score required between two localized characters to recognize these
characters as coherent word.</p>
<p>
<span class="pardesc"><span class="parcat">Value range:
      </span></span> <span title="77" style="vertical-align:-0.37221em" class="math"><!-- Created by MetaPost 1.902 on 2023.05.15:2033 --><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" version="1.1" width="3.35168em" height="1.12127em" viewBox="0 0 53.626907 17.940399">
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    </g>
    <g transform="scale(0.009963,0.009963)" id="GLYPHcmr10_93">
      <path style="fill-rule: evenodd;" d="M159.000000 -750.000000L22.000000 -750.000000L22.000000 -710.000000L119.000000 -710.000000L119.000000 210.000000L22.000000 210.000000L22.000000 250.000000L159.000000 250.000000"></path>
    </g>
    <g transform="scale(0.009963,0.009963)" id="GLYPHcmsy10_50">
      <path style="fill-rule: evenodd;" d="M548.000000 -230.000000C565.000000 -230.000000,583.000000 -230.000000,583.000000 -250.000000C583.000000 -270.000000,565.000000 -270.000000,548.000000 -270.000000L124.000000 -270.000000C136.000000 -404.000000,251.000000 -500.000000,392.000000 -500.000000L548.000000 -500.000000C565.000000 -500.000000,583.000000 -500.000000,583.000000 -520.000000C583.000000 -540.000000,565.000000 -540.000000,548.000000 -540.000000L390.000000 -540.000000C219.000000 -540.000000,83.000000 -410.000000,83.000000 -250.000000C83.000000 -90.000000,219.000000 40.000000,390.000000 40.000000L548.000000 40.000000C565.000000 40.000000,583.000000 40.000000,583.000000 20.000000C583.000000 -0.000000,565.000000 -0.000000,548.000000 -0.000000L392.000000 -0.000000C251.000000 -0.000000,136.000000 -96.000000,124.000000 -230.000000"></path>
    </g>
    <g transform="scale(0.009963,0.009963)" id="GLYPHcmmi10_59">
      <path style="fill-rule: evenodd;" d="M203.000000 -1.000000C203.000000 -67.000000,178.000000 -106.000000,139.000000 -106.000000C106.000000 -106.000000,86.000000 -81.000000,86.000000 -53.000000C86.000000 -26.000000,106.000000 -0.000000,139.000000 -0.000000C151.000000 -0.000000,164.000000 -4.000000,174.000000 -13.000000C177.000000 -15.000000,178.000000 -16.000000,179.000000 -16.000000C180.000000 -16.000000,181.000000 -15.000000,181.000000 -1.000000C181.000000 73.000000,146.000000 133.000000,113.000000 166.000000C102.000000 177.000000,102.000000 179.000000,102.000000 182.000000C102.000000 189.000000,107.000000 193.000000,112.000000 193.000000C123.000000 193.000000,203.000000 116.000000,203.000000 -1.000000"></path>
    </g>
    <g transform="scale(0.009963,0.009963)" id="GLYPHcmti10_48">
      <path style="fill-rule: evenodd;" d="M555.000000 -496.000000C555.000000 -536.000000,550.000000 -666.000000,421.000000 -666.000000C349.000000 -666.000000,269.000000 -619.000000,209.000000 -505.000000C160.000000 -412.000000,117.000000 -237.000000,117.000000 -148.000000C117.000000 -117.000000,117.000000 22.000000,251.000000 22.000000C317.000000 22.000000,411.000000 -19.000000,476.000000 -164.000000C517.000000 -257.000000,555.000000 -415.000000,555.000000 -496.000000M256.000000 -0.000000C224.000000 -0.000000,181.000000 -20.000000,181.000000 -98.000000C181.000000 -180.000000,256.000000 -475.000000,291.000000 -547.000000C328.000000 -622.000000,382.000000 -644.000000,416.000000 -644.000000C457.000000 -644.000000,493.000000 -614.000000,493.000000 -550.000000C493.000000 -476.000000,423.000000 -193.000000,380.000000 -98.000000C358.000000 -51.000000,308.000000 -0.000000,256.000000 -0.000000"></path>
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    <g transform="scale(0.009963,0.009963)" id="GLYPHcmti10_49">
      <path style="fill-rule: evenodd;" d="M458.000000 -641.000000C459.000000 -644.000000,461.000000 -652.000000,461.000000 -654.000000C461.000000 -662.000000,455.000000 -666.000000,449.000000 -666.000000C443.000000 -666.000000,442.000000 -665.000000,430.000000 -650.000000C353.000000 -547.000000,283.000000 -540.000000,254.000000 -537.000000C249.000000 -536.000000,238.000000 -535.000000,238.000000 -518.000000C238.000000 -506.000000,250.000000 -506.000000,254.000000 -506.000000C269.000000 -506.000000,318.000000 -512.000000,365.000000 -547.000000L247.000000 -73.000000C239.000000 -41.000000,231.000000 -31.000000,153.000000 -31.000000L145.000000 -31.000000C128.000000 -31.000000,117.000000 -31.000000,117.000000 -12.000000C117.000000 -0.000000,128.000000 -0.000000,132.000000 -0.000000L263.000000 -0.000000L175.000000 -0.000000L220.000000 -3.000000L263.000000 -3.000000L307.000000 -3.000000L353.000000 -0.000000L397.000000 -0.000000C404.000000 -0.000000,417.000000 -0.000000,417.000000 -19.000000C417.000000 -31.000000,407.000000 -31.000000,391.000000 -31.000000L383.000000 -31.000000C370.000000 -31.000000,353.000000 -32.000000,340.000000 -33.000000C318.000000 -36.000000,312.000000 -37.000000,312.000000 -51.000000C312.000000 -57.000000,314.000000 -66.000000,315.000000 -70.000000"></path>
    </g>
  </defs>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,0.202530 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmsy10_50"></use>
  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,15.257156 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmr10_91"></use>
  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,19.684998 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmti10_48"></use>
  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,29.993042 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmmi10_59"></use>
  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,37.077545 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmti10_49"></use>
  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,47.385590 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmr10_93"></use>
  </g>
</svg></span>.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i>0.3</i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_min_word_area'</span><span data-if="c" style="display:none">"detection_min_word_area"</span><span data-if="cpp" style="display:none">"detection_min_word_area"</span><span data-if="com" style="display:none">"detection_min_word_area"</span><span data-if="dotnet" style="display:none">"detection_min_word_area"</span><span data-if="python" style="display:none">"detection_min_word_area"</span></i>:</b></dt>
<dd>
<p>

The parameter <i><span data-if="hdevelop" style="display:inline">'detection_min_word_area'</span><span data-if="c" style="display:none">"detection_min_word_area"</span><span data-if="cpp" style="display:none">"detection_min_word_area"</span><span data-if="com" style="display:none">"detection_min_word_area"</span><span data-if="dotnet" style="display:none">"detection_min_word_area"</span><span data-if="python" style="display:none">"detection_min_word_area"</span></i> defines the minimum size
that a localized word must have in order to be suggested.
This parameter can be used to filter suggestions that are too small.</p>
<p>
<span class="pardesc"><span class="parcat">Value range:
      </span></span> <span title="78" style="vertical-align:-0.211713em" class="math"><!-- Created by MetaPost 1.902 on 2023.05.15:2033 --><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" version="1.1" width="1.82186em" height="0.902503em" viewBox="0 0 29.149719 14.440048">
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      <path style="fill-rule: evenodd;" d="M555.000000 -496.000000C555.000000 -536.000000,550.000000 -666.000000,421.000000 -666.000000C349.000000 -666.000000,269.000000 -619.000000,209.000000 -505.000000C160.000000 -412.000000,117.000000 -237.000000,117.000000 -148.000000C117.000000 -117.000000,117.000000 22.000000,251.000000 22.000000C317.000000 22.000000,411.000000 -19.000000,476.000000 -164.000000C517.000000 -257.000000,555.000000 -415.000000,555.000000 -496.000000M256.000000 -0.000000C224.000000 -0.000000,181.000000 -20.000000,181.000000 -98.000000C181.000000 -180.000000,256.000000 -475.000000,291.000000 -547.000000C328.000000 -622.000000,382.000000 -644.000000,416.000000 -644.000000C457.000000 -644.000000,493.000000 -614.000000,493.000000 -550.000000C493.000000 -476.000000,423.000000 -193.000000,380.000000 -98.000000C358.000000 -51.000000,308.000000 -0.000000,256.000000 -0.000000"></path>
    </g>
  </defs>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,0.441132 11.052643)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmsy10_21"></use>
  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,17.266800 11.052643)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
    <use xlink:href="#GLYPHcmti10_48"></use>
  </g>
</svg></span>.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i>10</i>.
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_min_word_score'</span><span data-if="c" style="display:none">"detection_min_word_score"</span><span data-if="cpp" style="display:none">"detection_min_word_score"</span><span data-if="com" style="display:none">"detection_min_word_score"</span><span data-if="dotnet" style="display:none">"detection_min_word_score"</span><span data-if="python" style="display:none">"detection_min_word_score"</span></i>:</b></dt>
<dd>
<p>

The parameter <i><span data-if="hdevelop" style="display:inline">'detection_min_word_score'</span><span data-if="c" style="display:none">"detection_min_word_score"</span><span data-if="cpp" style="display:none">"detection_min_word_score"</span><span data-if="com" style="display:none">"detection_min_word_score"</span><span data-if="dotnet" style="display:none">"detection_min_word_score"</span><span data-if="python" style="display:none">"detection_min_word_score"</span></i> defines the minimum
score a localized instance must contain to be suggested as valid word.
With this parameter uncertain words can be filtered out.</p>
<p>
<span class="pardesc"><span class="parcat">Value range:
      </span></span> <span title="79" style="vertical-align:-0.37221em" class="math"><!-- Created by MetaPost 1.902 on 2023.05.15:2033 --><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" version="1.1" width="3.35168em" height="1.12127em" viewBox="0 0 53.626907 17.940399">
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  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,29.993042 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
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</svg></span>.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i>0.7</i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_model'</span><span data-if="c" style="display:none">"detection_model"</span><span data-if="cpp" style="display:none">"detection_model"</span><span data-if="com" style="display:none">"detection_model"</span><span data-if="dotnet" style="display:none">"detection_model"</span><span data-if="python" style="display:none">"detection_model"</span></i>:</b></dt>
<dd>
<p>

该算子 <code><span data-if="hdevelop" style="display:inline">get_deep_ocr_param</span><span data-if="c" style="display:none">get_deep_ocr_param</span><span data-if="cpp" style="display:none">GetDeepOcrParam</span><span data-if="com" style="display:none">GetDeepOcrParam</span><span data-if="dotnet" style="display:none">GetDeepOcrParam</span><span data-if="python" style="display:none">get_deep_ocr_param</span></code> returns the handle of the Deep
OCR model component for word detection.
Using <a href="set_deep_ocr_param.html"><code><span data-if="hdevelop" style="display:inline">set_deep_ocr_param</span><span data-if="c" style="display:none">set_deep_ocr_param</span><span data-if="cpp" style="display:none">SetDeepOcrParam</span><span data-if="com" style="display:none">SetDeepOcrParam</span><span data-if="dotnet" style="display:none">SetDeepOcrParam</span><span data-if="python" style="display:none">set_deep_ocr_param</span></code></a> it is possible to either specify a handle,
filename or special string. As a special string only <i><span data-if="hdevelop" style="display:inline">'default'</span><span data-if="c" style="display:none">"default"</span><span data-if="cpp" style="display:none">"default"</span><span data-if="com" style="display:none">"default"</span><span data-if="dotnet" style="display:none">"default"</span><span data-if="python" style="display:none">"default"</span></i>
and <i><span data-if="hdevelop" style="display:inline">'compact'</span><span data-if="c" style="display:none">"compact"</span><span data-if="cpp" style="display:none">"compact"</span><span data-if="com" style="display:none">"compact"</span><span data-if="dotnet" style="display:none">"compact"</span><span data-if="python" style="display:none">"compact"</span></i> are allowed. In case of <i><span data-if="hdevelop" style="display:inline">'default'</span><span data-if="c" style="display:none">"default"</span><span data-if="cpp" style="display:none">"default"</span><span data-if="com" style="display:none">"default"</span><span data-if="dotnet" style="display:none">"default"</span><span data-if="python" style="display:none">"default"</span></i> the
default pretrained word detection component is loaded
(i.e. <i><span data-if="hdevelop" style="display:inline">'pretrained_deep_ocr_detection.hdl'</span><span data-if="c" style="display:none">"pretrained_deep_ocr_detection.hdl"</span><span data-if="cpp" style="display:none">"pretrained_deep_ocr_detection.hdl"</span><span data-if="com" style="display:none">"pretrained_deep_ocr_detection.hdl"</span><span data-if="dotnet" style="display:none">"pretrained_deep_ocr_detection.hdl"</span><span data-if="python" style="display:none">"pretrained_deep_ocr_detection.hdl"</span></i>).  In case of
<i><span data-if="hdevelop" style="display:inline">'compact'</span><span data-if="c" style="display:none">"compact"</span><span data-if="cpp" style="display:none">"compact"</span><span data-if="com" style="display:none">"compact"</span><span data-if="dotnet" style="display:none">"compact"</span><span data-if="python" style="display:none">"compact"</span></i>, a more efficient word detection component
is loaded (i.e. <i><span data-if="hdevelop" style="display:inline">'pretrained_deep_ocr_detection_compact.hdl'</span><span data-if="c" style="display:none">"pretrained_deep_ocr_detection_compact.hdl"</span><span data-if="cpp" style="display:none">"pretrained_deep_ocr_detection_compact.hdl"</span><span data-if="com" style="display:none">"pretrained_deep_ocr_detection_compact.hdl"</span><span data-if="dotnet" style="display:none">"pretrained_deep_ocr_detection_compact.hdl"</span><span data-if="python" style="display:none">"pretrained_deep_ocr_detection_compact.hdl"</span></i>).
If the given value is a string the model is loaded internally and the
batch size is set to <i>1</i>.</p>
<p>
<span class="pardesc"><span class="parcat">Suggested values:
      </span></span>  <i><span data-if="hdevelop" style="display:inline">'default'</span><span data-if="c" style="display:none">"default"</span><span data-if="cpp" style="display:none">"default"</span><span data-if="com" style="display:none">"default"</span><span data-if="dotnet" style="display:none">"default"</span><span data-if="python" style="display:none">"default"</span></i>, <i><span data-if="hdevelop" style="display:inline">'compact'</span><span data-if="c" style="display:none">"compact"</span><span data-if="cpp" style="display:none">"compact"</span><span data-if="com" style="display:none">"compact"</span><span data-if="dotnet" style="display:none">"compact"</span><span data-if="python" style="display:none">"compact"</span></i>, filename.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i><span data-if="hdevelop" style="display:inline">'default'</span><span data-if="c" style="display:none">"default"</span><span data-if="cpp" style="display:none">"default"</span><span data-if="com" style="display:none">"default"</span><span data-if="dotnet" style="display:none">"default"</span><span data-if="python" style="display:none">"default"</span></i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_orientation'</span><span data-if="c" style="display:none">"detection_orientation"</span><span data-if="cpp" style="display:none">"detection_orientation"</span><span data-if="com" style="display:none">"detection_orientation"</span><span data-if="dotnet" style="display:none">"detection_orientation"</span><span data-if="python" style="display:none">"detection_orientation"</span></i>:</b></dt>
<dd>
<p>

This parameter allows to set a predefined orientation angle for the word
detection. To revert to default behavior using the internal orientation
estimation, <i><span data-if="hdevelop" style="display:inline">'detection_orientation'</span><span data-if="c" style="display:none">"detection_orientation"</span><span data-if="cpp" style="display:none">"detection_orientation"</span><span data-if="com" style="display:none">"detection_orientation"</span><span data-if="dotnet" style="display:none">"detection_orientation"</span><span data-if="python" style="display:none">"detection_orientation"</span></i> is set to <i><span data-if="hdevelop" style="display:inline">'auto'</span><span data-if="c" style="display:none">"auto"</span><span data-if="cpp" style="display:none">"auto"</span><span data-if="com" style="display:none">"auto"</span><span data-if="dotnet" style="display:none">"auto"</span><span data-if="python" style="display:none">"auto"</span></i>.</p>
<p>
<span class="pardesc"><span class="parcat">Value range:
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  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,28.550323 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
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  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,35.634842 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
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  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,45.293106 11.985046)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
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  </g>
</svg></span>.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i><span data-if="hdevelop" style="display:inline">'auto'</span><span data-if="c" style="display:none">"auto"</span><span data-if="cpp" style="display:none">"auto"</span><span data-if="com" style="display:none">"auto"</span><span data-if="dotnet" style="display:none">"auto"</span><span data-if="python" style="display:none">"auto"</span></i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_sort_by_line'</span><span data-if="c" style="display:none">"detection_sort_by_line"</span><span data-if="cpp" style="display:none">"detection_sort_by_line"</span><span data-if="com" style="display:none">"detection_sort_by_line"</span><span data-if="dotnet" style="display:none">"detection_sort_by_line"</span><span data-if="python" style="display:none">"detection_sort_by_line"</span></i>:</b></dt>
<dd>
<p>

The words are sorted line-wise based on the orientation of the localized
word instances. If a sorting in row and column direction is preferred, the
parameter <i><span data-if="hdevelop" style="display:inline">'detection_sort_by_line'</span><span data-if="c" style="display:none">"detection_sort_by_line"</span><span data-if="cpp" style="display:none">"detection_sort_by_line"</span><span data-if="com" style="display:none">"detection_sort_by_line"</span><span data-if="dotnet" style="display:none">"detection_sort_by_line"</span><span data-if="python" style="display:none">"detection_sort_by_line"</span></i> has to be set to
<i><span data-if="hdevelop" style="display:inline">'false'</span><span data-if="c" style="display:none">"false"</span><span data-if="cpp" style="display:none">"false"</span><span data-if="com" style="display:none">"false"</span><span data-if="dotnet" style="display:none">"false"</span><span data-if="python" style="display:none">"false"</span></i>.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i><span data-if="hdevelop" style="display:inline">'true'</span><span data-if="c" style="display:none">"true"</span><span data-if="cpp" style="display:none">"true"</span><span data-if="com" style="display:none">"true"</span><span data-if="dotnet" style="display:none">"true"</span><span data-if="python" style="display:none">"true"</span></i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_tiling'</span><span data-if="c" style="display:none">"detection_tiling"</span><span data-if="cpp" style="display:none">"detection_tiling"</span><span data-if="com" style="display:none">"detection_tiling"</span><span data-if="dotnet" style="display:none">"detection_tiling"</span><span data-if="python" style="display:none">"detection_tiling"</span></i>:</b></dt>
<dd>
<p>

The input image is automatically split into overlapping tile images of
size <i><span data-if="hdevelop" style="display:inline">'detection_image_size'</span><span data-if="c" style="display:none">"detection_image_size"</span><span data-if="cpp" style="display:none">"detection_image_size"</span><span data-if="com" style="display:none">"detection_image_size"</span><span data-if="dotnet" style="display:none">"detection_image_size"</span><span data-if="python" style="display:none">"detection_image_size"</span></i>, which are processed separately by
the detection component. This allows processing images that are much
larger than the actual <i><span data-if="hdevelop" style="display:inline">'detection_image_size'</span><span data-if="c" style="display:none">"detection_image_size"</span><span data-if="cpp" style="display:none">"detection_image_size"</span><span data-if="com" style="display:none">"detection_image_size"</span><span data-if="dotnet" style="display:none">"detection_image_size"</span><span data-if="python" style="display:none">"detection_image_size"</span></i> without having to
zoom the input image.
Thus, if <i><span data-if="hdevelop" style="display:inline">'detection_tiling'</span><span data-if="c" style="display:none">"detection_tiling"</span><span data-if="cpp" style="display:none">"detection_tiling"</span><span data-if="com" style="display:none">"detection_tiling"</span><span data-if="dotnet" style="display:none">"detection_tiling"</span><span data-if="python" style="display:none">"detection_tiling"</span></i> = {'true'}, the input image will
not be zoomed before processing it.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i><span data-if="hdevelop" style="display:inline">'false'</span><span data-if="c" style="display:none">"false"</span><span data-if="cpp" style="display:none">"false"</span><span data-if="com" style="display:none">"false"</span><span data-if="dotnet" style="display:none">"false"</span><span data-if="python" style="display:none">"false"</span></i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'detection_tiling_overlap'</span><span data-if="c" style="display:none">"detection_tiling_overlap"</span><span data-if="cpp" style="display:none">"detection_tiling_overlap"</span><span data-if="com" style="display:none">"detection_tiling_overlap"</span><span data-if="dotnet" style="display:none">"detection_tiling_overlap"</span><span data-if="python" style="display:none">"detection_tiling_overlap"</span></i>:</b></dt>
<dd>
<p>

This parameter defines how much neighboring tiles overlap when input
images are split (see <i><span data-if="hdevelop" style="display:inline">'detection_tiling'</span><span data-if="c" style="display:none">"detection_tiling"</span><span data-if="cpp" style="display:none">"detection_tiling"</span><span data-if="com" style="display:none">"detection_tiling"</span><span data-if="dotnet" style="display:none">"detection_tiling"</span><span data-if="python" style="display:none">"detection_tiling"</span></i>). The overlap
is given in pixels.</p>
<p>
<span class="pardesc"><span class="parcat">Value range:
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  </defs>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,0.441132 11.052643)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
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  </g>
  <g transform="matrix(1.600006,-0.000000,-0.000000,1.600006,17.266800 11.052643)" style="fill: rgb(0.000000%,0.000000%,0.000000%);">
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  </g>
</svg></span>.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i>64</i>
</p>
</dd>
</dl>

</dd>

<dt><b>Recognition component:</b></dt>
<dd>
<p>

</p>
<dl class="generic">


<dt><b><i><span data-if="hdevelop" style="display:inline">'recognition_alphabet'</span><span data-if="c" style="display:none">"recognition_alphabet"</span><span data-if="cpp" style="display:none">"recognition_alphabet"</span><span data-if="com" style="display:none">"recognition_alphabet"</span><span data-if="dotnet" style="display:none">"recognition_alphabet"</span><span data-if="python" style="display:none">"recognition_alphabet"</span></i>:</b></dt>
<dd>
<p>

The character set that can be recognized by the Deep OCR model.
</p>
<p>It contains all characters that are not mapped to the Blank character
of the internal alphabet (see parameters
<i><span data-if="hdevelop" style="display:inline">'recognition_alphabet_mapping'</span><span data-if="c" style="display:none">"recognition_alphabet_mapping"</span><span data-if="cpp" style="display:none">"recognition_alphabet_mapping"</span><span data-if="com" style="display:none">"recognition_alphabet_mapping"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_mapping"</span><span data-if="python" style="display:none">"recognition_alphabet_mapping"</span></i>
and <i><span data-if="hdevelop" style="display:inline">'recognition_alphabet_internal'</span><span data-if="c" style="display:none">"recognition_alphabet_internal"</span><span data-if="cpp" style="display:none">"recognition_alphabet_internal"</span><span data-if="com" style="display:none">"recognition_alphabet_internal"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_internal"</span><span data-if="python" style="display:none">"recognition_alphabet_internal"</span></i>).
</p>
<p>The alphabet can be changed or extended if needed. Changing the
alphabet with this parameter will edit the internal alphabet and
mapping in such a way that it tries to keep the length of the internal
alphabet unchanged.
After changing the alphabet, it is recommended to retrain the model on
application specific data (see the HDevelop example
<code>deep_ocr_recognition_training_workflow.hdev</code>).
Previously unknown characters will need more training data.
</p>
<p>Note, that if the length of the internal alphabet changes, the last
model layers have to be randomly initialized and thus the output of the
model will be random strings (see
<i><span data-if="hdevelop" style="display:inline">'recognition_alphabet_internal'</span><span data-if="c" style="display:none">"recognition_alphabet_internal"</span><span data-if="cpp" style="display:none">"recognition_alphabet_internal"</span><span data-if="com" style="display:none">"recognition_alphabet_internal"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_internal"</span><span data-if="python" style="display:none">"recognition_alphabet_internal"</span></i>). In that case it is required to
retrain the model.
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'recognition_alphabet_internal'</span><span data-if="c" style="display:none">"recognition_alphabet_internal"</span><span data-if="cpp" style="display:none">"recognition_alphabet_internal"</span><span data-if="com" style="display:none">"recognition_alphabet_internal"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_internal"</span><span data-if="python" style="display:none">"recognition_alphabet_internal"</span></i>:</b></dt>
<dd>
<p>

The full character set which the Deep OCR recognition component has
been trained on.
</p>
<p>The first character of the internal alphabet is a special character.
In the pretrained model this character is specified as Blank
(U+2800) and is not to be confused with a space.
The Blank is never returned in a word output but can occur in the
reported character candidates. It is required and cannot be omitted.
If the internal alphabet is changed, the first character has to be
the Blank.
Furthermore, if <i><span data-if="hdevelop" style="display:inline">'recognition_alphabet'</span><span data-if="c" style="display:none">"recognition_alphabet"</span><span data-if="cpp" style="display:none">"recognition_alphabet"</span><span data-if="com" style="display:none">"recognition_alphabet"</span><span data-if="dotnet" style="display:none">"recognition_alphabet"</span><span data-if="python" style="display:none">"recognition_alphabet"</span></i> is used to change
the alphabet, the Blank symbol is added automatically to the
character set.
</p>
<p>The length of this tuple corresponds to the depth of the last
convolution layer in the model. If the length changes, the last
convolution layer and all layers after it have to be resized and
potentially reinitialized randomly. After such a change, it is required
to retrain the model (see HDevelop example
<code>deep_ocr_recognition_training_workflow.hdev</code>).
</p>
<p>It is recommend to use the parameter <i><span data-if="hdevelop" style="display:inline">'recognition_alphabet'</span><span data-if="c" style="display:none">"recognition_alphabet"</span><span data-if="cpp" style="display:none">"recognition_alphabet"</span><span data-if="com" style="display:none">"recognition_alphabet"</span><span data-if="dotnet" style="display:none">"recognition_alphabet"</span><span data-if="python" style="display:none">"recognition_alphabet"</span></i> to
change the alphabet, as it will automatically try to preserve the
length of the internal alphabet.
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'recognition_alphabet_mapping'</span><span data-if="c" style="display:none">"recognition_alphabet_mapping"</span><span data-if="cpp" style="display:none">"recognition_alphabet_mapping"</span><span data-if="com" style="display:none">"recognition_alphabet_mapping"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_mapping"</span><span data-if="python" style="display:none">"recognition_alphabet_mapping"</span></i>:</b></dt>
<dd>
<p>

Tuple of integer indices.
</p>
<p>It is a mapping that is applied by the model during the decoding step
of each word. The mapping overwrites a character of
<i><span data-if="hdevelop" style="display:inline">'recognition_alphabet_internal'</span><span data-if="c" style="display:none">"recognition_alphabet_internal"</span><span data-if="cpp" style="display:none">"recognition_alphabet_internal"</span><span data-if="com" style="display:none">"recognition_alphabet_internal"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_internal"</span><span data-if="python" style="display:none">"recognition_alphabet_internal"</span></i> with
the character at the specified index in
<i><span data-if="hdevelop" style="display:inline">'recognition_alphabet_internal'</span><span data-if="c" style="display:none">"recognition_alphabet_internal"</span><span data-if="cpp" style="display:none">"recognition_alphabet_internal"</span><span data-if="com" style="display:none">"recognition_alphabet_internal"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_internal"</span><span data-if="python" style="display:none">"recognition_alphabet_internal"</span></i>.
</p>
<p>In the decoding step each prediction is mapped according to the index
specified in this tuple.
The tuple has to be of same length as the tuple
<i><span data-if="hdevelop" style="display:inline">'recognition_alphabet_internal'</span><span data-if="c" style="display:none">"recognition_alphabet_internal"</span><span data-if="cpp" style="display:none">"recognition_alphabet_internal"</span><span data-if="com" style="display:none">"recognition_alphabet_internal"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_internal"</span><span data-if="python" style="display:none">"recognition_alphabet_internal"</span></i>. Each integer index of the
mapping has to be within <i>0</i> and
|<i><span data-if="hdevelop" style="display:inline">'recognition_alphabet_internal'</span><span data-if="c" style="display:none">"recognition_alphabet_internal"</span><span data-if="cpp" style="display:none">"recognition_alphabet_internal"</span><span data-if="com" style="display:none">"recognition_alphabet_internal"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_internal"</span><span data-if="python" style="display:none">"recognition_alphabet_internal"</span></i>|-1.
</p>
<p>In some applications it can be helpful to map certain characters onto
other characters. E.g. if only numeric words occur in an application it
might be helpful to map the character "O" to the "0" character
without the need to retrain the model.
</p>
<p>If an entry contains a <i>0</i>, the corresponding character in
<i><span data-if="hdevelop" style="display:inline">'recognition_alphabet_internal'</span><span data-if="c" style="display:none">"recognition_alphabet_internal"</span><span data-if="cpp" style="display:none">"recognition_alphabet_internal"</span><span data-if="com" style="display:none">"recognition_alphabet_internal"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_internal"</span><span data-if="python" style="display:none">"recognition_alphabet_internal"</span></i> will not be decoded in the
word.
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'recognition_batch_size'</span><span data-if="c" style="display:none">"recognition_batch_size"</span><span data-if="cpp" style="display:none">"recognition_batch_size"</span><span data-if="com" style="display:none">"recognition_batch_size"</span><span data-if="dotnet" style="display:none">"recognition_batch_size"</span><span data-if="python" style="display:none">"recognition_batch_size"</span></i>:</b></dt>
<dd>
<p>

Number of images in a batch that is transferred to device memory and
processed in parallel in the recognition component. For further
details, please refer to the reference documentation of
<a href="apply_dl_model.html"><code><span data-if="hdevelop" style="display:inline">apply_dl_model</span><span data-if="c" style="display:none">apply_dl_model</span><span data-if="cpp" style="display:none">ApplyDlModel</span><span data-if="com" style="display:none">ApplyDlModel</span><span data-if="dotnet" style="display:none">ApplyDlModel</span><span data-if="python" style="display:none">apply_dl_model</span></code></a> with respect to the parameter
<i><span data-if="hdevelop" style="display:inline">'batch_size'</span><span data-if="c" style="display:none">"batch_size"</span><span data-if="cpp" style="display:none">"batch_size"</span><span data-if="com" style="display:none">"batch_size"</span><span data-if="dotnet" style="display:none">"batch_size"</span><span data-if="python" style="display:none">"batch_size"</span></i>. This parameter can be used to optimize the
runtime of <a href="apply_deep_ocr.html"><code><span data-if="hdevelop" style="display:inline">apply_deep_ocr</span><span data-if="c" style="display:none">apply_deep_ocr</span><span data-if="cpp" style="display:none">ApplyDeepOcr</span><span data-if="com" style="display:none">ApplyDeepOcr</span><span data-if="dotnet" style="display:none">ApplyDeepOcr</span><span data-if="python" style="display:none">apply_deep_ocr</span></code></a> on a given dl device.  If the
recognition component has to process multiple inputs (words),
processing multiple inputs in parallel can result in a faster execution
of <a href="apply_deep_ocr.html"><code><span data-if="hdevelop" style="display:inline">apply_deep_ocr</span><span data-if="c" style="display:none">apply_deep_ocr</span><span data-if="cpp" style="display:none">ApplyDeepOcr</span><span data-if="com" style="display:none">ApplyDeepOcr</span><span data-if="dotnet" style="display:none">ApplyDeepOcr</span><span data-if="python" style="display:none">apply_deep_ocr</span></code></a>. Note, however, that a higher
<i><span data-if="hdevelop" style="display:inline">'recognition_batch_size'</span><span data-if="c" style="display:none">"recognition_batch_size"</span><span data-if="cpp" style="display:none">"recognition_batch_size"</span><span data-if="com" style="display:none">"recognition_batch_size"</span><span data-if="dotnet" style="display:none">"recognition_batch_size"</span><span data-if="python" style="display:none">"recognition_batch_size"</span></i> will require more device memory.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i>1</i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'recognition_device'</span><span data-if="c" style="display:none">"recognition_device"</span><span data-if="cpp" style="display:none">"recognition_device"</span><span data-if="com" style="display:none">"recognition_device"</span><span data-if="dotnet" style="display:none">"recognition_device"</span><span data-if="python" style="display:none">"recognition_device"</span></i>:</b></dt>
<dd>
<p>

This parameter will set the device on which the recognition component of
the Deep OCR model is executed. For a further description, see
<i><span data-if="hdevelop" style="display:inline">'device'</span><span data-if="c" style="display:none">"device"</span><span data-if="cpp" style="display:none">"device"</span><span data-if="com" style="display:none">"device"</span><span data-if="dotnet" style="display:none">"device"</span><span data-if="python" style="display:none">"device"</span></i>.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> The same value as for <i><span data-if="hdevelop" style="display:inline">'device'</span><span data-if="c" style="display:none">"device"</span><span data-if="cpp" style="display:none">"device"</span><span data-if="com" style="display:none">"device"</span><span data-if="dotnet" style="display:none">"device"</span><span data-if="python" style="display:none">"device"</span></i>.
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'recognition_image_dimensions'</span><span data-if="c" style="display:none">"recognition_image_dimensions"</span><span data-if="cpp" style="display:none">"recognition_image_dimensions"</span><span data-if="com" style="display:none">"recognition_image_dimensions"</span><span data-if="dotnet" style="display:none">"recognition_image_dimensions"</span><span data-if="python" style="display:none">"recognition_image_dimensions"</span></i>:</b></dt>
<dd>
<p>

Tuple containing the image dimensions (<i><span data-if="hdevelop" style="display:inline">'recognition_image_width'</span><span data-if="c" style="display:none">"recognition_image_width"</span><span data-if="cpp" style="display:none">"recognition_image_width"</span><span data-if="com" style="display:none">"recognition_image_width"</span><span data-if="dotnet" style="display:none">"recognition_image_width"</span><span data-if="python" style="display:none">"recognition_image_width"</span></i>,
<i><span data-if="hdevelop" style="display:inline">'recognition_image_height'</span><span data-if="c" style="display:none">"recognition_image_height"</span><span data-if="cpp" style="display:none">"recognition_image_height"</span><span data-if="com" style="display:none">"recognition_image_height"</span><span data-if="dotnet" style="display:none">"recognition_image_height"</span><span data-if="python" style="display:none">"recognition_image_height"</span></i>, number of channels)
the recognition component will process.</p>
<p>
This means, the network will first zoom the input image part to
<i><span data-if="hdevelop" style="display:inline">'recognition_image_height'</span><span data-if="c" style="display:none">"recognition_image_height"</span><span data-if="cpp" style="display:none">"recognition_image_height"</span><span data-if="com" style="display:none">"recognition_image_height"</span><span data-if="dotnet" style="display:none">"recognition_image_height"</span><span data-if="python" style="display:none">"recognition_image_height"</span></i> while maintaining the aspect ratio
of the input. If the width of the resulting image is smaller than
<i><span data-if="hdevelop" style="display:inline">'recognition_image_width'</span><span data-if="c" style="display:none">"recognition_image_width"</span><span data-if="cpp" style="display:none">"recognition_image_width"</span><span data-if="com" style="display:none">"recognition_image_width"</span><span data-if="dotnet" style="display:none">"recognition_image_width"</span><span data-if="python" style="display:none">"recognition_image_width"</span></i>, the image part is padded with
gray value <i>0</i> on the right. If it is larger, the image is
zoomed to <i><span data-if="hdevelop" style="display:inline">'recognition_image_width'</span><span data-if="c" style="display:none">"recognition_image_width"</span><span data-if="cpp" style="display:none">"recognition_image_width"</span><span data-if="com" style="display:none">"recognition_image_width"</span><span data-if="dotnet" style="display:none">"recognition_image_width"</span><span data-if="python" style="display:none">"recognition_image_width"</span></i>.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> [<i>120</i>, <i>32</i>, <i>1</i>]
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'recognition_image_height'</span><span data-if="c" style="display:none">"recognition_image_height"</span><span data-if="cpp" style="display:none">"recognition_image_height"</span><span data-if="com" style="display:none">"recognition_image_height"</span><span data-if="dotnet" style="display:none">"recognition_image_height"</span><span data-if="python" style="display:none">"recognition_image_height"</span></i>:</b></dt>
<dd>
<p>

Height of the images the recognition component will process.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i>32</i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'recognition_image_width'</span><span data-if="c" style="display:none">"recognition_image_width"</span><span data-if="cpp" style="display:none">"recognition_image_width"</span><span data-if="com" style="display:none">"recognition_image_width"</span><span data-if="dotnet" style="display:none">"recognition_image_width"</span><span data-if="python" style="display:none">"recognition_image_width"</span></i>:</b></dt>
<dd>
<p>

Width of the images the recognition component will process.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i>120</i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'recognition_model'</span><span data-if="c" style="display:none">"recognition_model"</span><span data-if="cpp" style="display:none">"recognition_model"</span><span data-if="com" style="display:none">"recognition_model"</span><span data-if="dotnet" style="display:none">"recognition_model"</span><span data-if="python" style="display:none">"recognition_model"</span></i>:</b></dt>
<dd>
<p>

该算子 <code><span data-if="hdevelop" style="display:inline">get_deep_ocr_param</span><span data-if="c" style="display:none">get_deep_ocr_param</span><span data-if="cpp" style="display:none">GetDeepOcrParam</span><span data-if="com" style="display:none">GetDeepOcrParam</span><span data-if="dotnet" style="display:none">GetDeepOcrParam</span><span data-if="python" style="display:none">get_deep_ocr_param</span></code> returns the handle of the Deep
OCR model component for word recognition.</p>
<p>
Using <a href="set_deep_ocr_param.html"><code><span data-if="hdevelop" style="display:inline">set_deep_ocr_param</span><span data-if="c" style="display:none">set_deep_ocr_param</span><span data-if="cpp" style="display:none">SetDeepOcrParam</span><span data-if="com" style="display:none">SetDeepOcrParam</span><span data-if="dotnet" style="display:none">SetDeepOcrParam</span><span data-if="python" style="display:none">set_deep_ocr_param</span></code></a> it is possible to either specify a
handle, filename or <i><span data-if="hdevelop" style="display:inline">'default'</span><span data-if="c" style="display:none">"default"</span><span data-if="cpp" style="display:none">"default"</span><span data-if="com" style="display:none">"default"</span><span data-if="dotnet" style="display:none">"default"</span><span data-if="python" style="display:none">"default"</span></i>. In case of <i><span data-if="hdevelop" style="display:inline">'default'</span><span data-if="c" style="display:none">"default"</span><span data-if="cpp" style="display:none">"default"</span><span data-if="com" style="display:none">"default"</span><span data-if="dotnet" style="display:none">"default"</span><span data-if="python" style="display:none">"default"</span></i> the
pretrained word recognition component is loaded (i.e.
<i><span data-if="hdevelop" style="display:inline">'pretrained_deep_ocr_recognition.hdl'</span><span data-if="c" style="display:none">"pretrained_deep_ocr_recognition.hdl"</span><span data-if="cpp" style="display:none">"pretrained_deep_ocr_recognition.hdl"</span><span data-if="com" style="display:none">"pretrained_deep_ocr_recognition.hdl"</span><span data-if="dotnet" style="display:none">"pretrained_deep_ocr_recognition.hdl"</span><span data-if="python" style="display:none">"pretrained_deep_ocr_recognition.hdl"</span></i>).
If the given value is a string the model is loaded internally and the
batch size is set to <i>1</i>.</p>
<p>
<span class="pardesc"><span class="parcat">Suggested values:
      </span></span>  <i><span data-if="hdevelop" style="display:inline">'default'</span><span data-if="c" style="display:none">"default"</span><span data-if="cpp" style="display:none">"default"</span><span data-if="com" style="display:none">"default"</span><span data-if="dotnet" style="display:none">"default"</span><span data-if="python" style="display:none">"default"</span></i>, filename.</p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i><span data-if="hdevelop" style="display:inline">'default'</span><span data-if="c" style="display:none">"default"</span><span data-if="cpp" style="display:none">"default"</span><span data-if="com" style="display:none">"default"</span><span data-if="dotnet" style="display:none">"default"</span><span data-if="python" style="display:none">"default"</span></i>
</p>
</dd>

<dt><b><i><span data-if="hdevelop" style="display:inline">'recognition_num_char_candidates'</span><span data-if="c" style="display:none">"recognition_num_char_candidates"</span><span data-if="cpp" style="display:none">"recognition_num_char_candidates"</span><span data-if="com" style="display:none">"recognition_num_char_candidates"</span><span data-if="dotnet" style="display:none">"recognition_num_char_candidates"</span><span data-if="python" style="display:none">"recognition_num_char_candidates"</span></i>:</b></dt>
<dd>
<p>

Controls the number of reported character candidates in the result of the
operator <a href="apply_deep_ocr.html"><code><span data-if="hdevelop" style="display:inline">apply_deep_ocr</span><span data-if="c" style="display:none">apply_deep_ocr</span><span data-if="cpp" style="display:none">ApplyDeepOcr</span><span data-if="com" style="display:none">ApplyDeepOcr</span><span data-if="dotnet" style="display:none">ApplyDeepOcr</span><span data-if="python" style="display:none">apply_deep_ocr</span></code></a>. </p>
<p>
<span class="pardesc"><span class="parcat">Default:
      </span></span> <i>3</i>
</p>
</dd>
</dl>

</dd>
</dl>
<h2 id="sec_execution">运行信息</h2>
<ul>
  <li>多线程类型:可重入(与非独占操作符并行运行)。</li>
<li>多线程作用域:全局(可以从任何线程调用)。</li>
  <li>未经并行化处理。</li>
</ul>
<h2 id="sec_parameters">参数表</h2>
  <div class="par">
<div class="parhead">
<span id="DeepOcrHandle" class="parname"><b><code><span data-if="hdevelop" style="display:inline">DeepOcrHandle</span><span data-if="c" style="display:none">DeepOcrHandle</span><span data-if="cpp" style="display:none">DeepOcrHandle</span><span data-if="com" style="display:none">DeepOcrHandle</span><span data-if="dotnet" style="display:none">deepOcrHandle</span><span data-if="python" style="display:none">deep_ocr_handle</span></code></b> (input_control)  </span><span>deep_ocr <code>→</code> <span data-if="dotnet" style="display:none"><a href="HDlModelOcr.html">HDlModelOcr</a>, </span><span data-if="dotnet" style="display:none"><a href="HTuple.html">HTuple</a></span><span data-if="python" style="display:none">HHandle</span><span data-if="cpp" style="display:none"><a href="HTuple.html">HTuple</a></span><span data-if="c" style="display:none">Htuple</span><span data-if="hdevelop" style="display:inline"> (handle)</span><span data-if="dotnet" style="display:none"> (<i>IntPtr</i>)</span><span data-if="cpp" style="display:none"> (<i>HHandle</i>)</span><span data-if="c" style="display:none"> (<i>handle</i>)</span></span>
</div>
<p class="pardesc">Handle of the Deep OCR model.</p>
</div>
  <div class="par">
<div class="parhead">
<span id="GenParamName" class="parname"><b><code><span data-if="hdevelop" style="display:inline">GenParamName</span><span data-if="c" style="display:none">GenParamName</span><span data-if="cpp" style="display:none">GenParamName</span><span data-if="com" style="display:none">GenParamName</span><span data-if="dotnet" style="display:none">genParamName</span><span data-if="python" style="display:none">gen_param_name</span></code></b> (input_control)  </span><span>attribute.name <code>→</code> <span data-if="dotnet" style="display:none"><a href="HTuple.html">HTuple</a></span><span data-if="python" style="display:none">str</span><span data-if="cpp" style="display:none"><a href="HTuple.html">HTuple</a></span><span data-if="c" style="display:none">Htuple</span><span data-if="hdevelop" style="display:inline"> (string)</span><span data-if="dotnet" style="display:none"> (<i>string</i>)</span><span data-if="cpp" style="display:none"> (<i>HString</i>)</span><span data-if="c" style="display:none"> (<i>char*</i>)</span></span>
</div>
<p class="pardesc">Name of the generic parameter.</p>
<p class="pardesc"><span class="parcat">Default:
      </span>
    <span data-if="hdevelop" style="display:inline">'recognition_model'</span>
    <span data-if="c" style="display:none">"recognition_model"</span>
    <span data-if="cpp" style="display:none">"recognition_model"</span>
    <span data-if="com" style="display:none">"recognition_model"</span>
    <span data-if="dotnet" style="display:none">"recognition_model"</span>
    <span data-if="python" style="display:none">"recognition_model"</span>
</p>
<p class="pardesc"><span class="parcat">List of values:
      </span><span data-if="hdevelop" style="display:inline">'detection_device'</span><span data-if="c" style="display:none">"detection_device"</span><span data-if="cpp" style="display:none">"detection_device"</span><span data-if="com" style="display:none">"detection_device"</span><span data-if="dotnet" style="display:none">"detection_device"</span><span data-if="python" style="display:none">"detection_device"</span>, <span data-if="hdevelop" style="display:inline">'detection_image_dimensions'</span><span data-if="c" style="display:none">"detection_image_dimensions"</span><span data-if="cpp" style="display:none">"detection_image_dimensions"</span><span data-if="com" style="display:none">"detection_image_dimensions"</span><span data-if="dotnet" style="display:none">"detection_image_dimensions"</span><span data-if="python" style="display:none">"detection_image_dimensions"</span>, <span data-if="hdevelop" style="display:inline">'detection_image_height'</span><span data-if="c" style="display:none">"detection_image_height"</span><span data-if="cpp" style="display:none">"detection_image_height"</span><span data-if="com" style="display:none">"detection_image_height"</span><span data-if="dotnet" style="display:none">"detection_image_height"</span><span data-if="python" style="display:none">"detection_image_height"</span>, <span data-if="hdevelop" style="display:inline">'detection_image_size'</span><span data-if="c" style="display:none">"detection_image_size"</span><span data-if="cpp" style="display:none">"detection_image_size"</span><span data-if="com" style="display:none">"detection_image_size"</span><span data-if="dotnet" style="display:none">"detection_image_size"</span><span data-if="python" style="display:none">"detection_image_size"</span>, <span data-if="hdevelop" style="display:inline">'detection_image_width'</span><span data-if="c" style="display:none">"detection_image_width"</span><span data-if="cpp" style="display:none">"detection_image_width"</span><span data-if="com" style="display:none">"detection_image_width"</span><span data-if="dotnet" style="display:none">"detection_image_width"</span><span data-if="python" style="display:none">"detection_image_width"</span>, <span data-if="hdevelop" style="display:inline">'detection_min_character_score'</span><span data-if="c" style="display:none">"detection_min_character_score"</span><span data-if="cpp" style="display:none">"detection_min_character_score"</span><span data-if="com" style="display:none">"detection_min_character_score"</span><span data-if="dotnet" style="display:none">"detection_min_character_score"</span><span data-if="python" style="display:none">"detection_min_character_score"</span>, <span data-if="hdevelop" style="display:inline">'detection_min_link_score'</span><span data-if="c" style="display:none">"detection_min_link_score"</span><span data-if="cpp" style="display:none">"detection_min_link_score"</span><span data-if="com" style="display:none">"detection_min_link_score"</span><span data-if="dotnet" style="display:none">"detection_min_link_score"</span><span data-if="python" style="display:none">"detection_min_link_score"</span>, <span data-if="hdevelop" style="display:inline">'detection_min_word_area'</span><span data-if="c" style="display:none">"detection_min_word_area"</span><span data-if="cpp" style="display:none">"detection_min_word_area"</span><span data-if="com" style="display:none">"detection_min_word_area"</span><span data-if="dotnet" style="display:none">"detection_min_word_area"</span><span data-if="python" style="display:none">"detection_min_word_area"</span>, <span data-if="hdevelop" style="display:inline">'detection_min_word_score'</span><span data-if="c" style="display:none">"detection_min_word_score"</span><span data-if="cpp" style="display:none">"detection_min_word_score"</span><span data-if="com" style="display:none">"detection_min_word_score"</span><span data-if="dotnet" style="display:none">"detection_min_word_score"</span><span data-if="python" style="display:none">"detection_min_word_score"</span>, <span data-if="hdevelop" style="display:inline">'detection_model'</span><span data-if="c" style="display:none">"detection_model"</span><span data-if="cpp" style="display:none">"detection_model"</span><span data-if="com" style="display:none">"detection_model"</span><span data-if="dotnet" style="display:none">"detection_model"</span><span data-if="python" style="display:none">"detection_model"</span>, <span data-if="hdevelop" style="display:inline">'detection_orientation'</span><span data-if="c" style="display:none">"detection_orientation"</span><span data-if="cpp" style="display:none">"detection_orientation"</span><span data-if="com" style="display:none">"detection_orientation"</span><span data-if="dotnet" style="display:none">"detection_orientation"</span><span data-if="python" style="display:none">"detection_orientation"</span>, <span data-if="hdevelop" style="display:inline">'detection_sort_by_line'</span><span data-if="c" style="display:none">"detection_sort_by_line"</span><span data-if="cpp" style="display:none">"detection_sort_by_line"</span><span data-if="com" style="display:none">"detection_sort_by_line"</span><span data-if="dotnet" style="display:none">"detection_sort_by_line"</span><span data-if="python" style="display:none">"detection_sort_by_line"</span>, <span data-if="hdevelop" style="display:inline">'detection_tiling'</span><span data-if="c" style="display:none">"detection_tiling"</span><span data-if="cpp" style="display:none">"detection_tiling"</span><span data-if="com" style="display:none">"detection_tiling"</span><span data-if="dotnet" style="display:none">"detection_tiling"</span><span data-if="python" style="display:none">"detection_tiling"</span>, <span data-if="hdevelop" style="display:inline">'detection_tiling_overlap'</span><span data-if="c" style="display:none">"detection_tiling_overlap"</span><span data-if="cpp" style="display:none">"detection_tiling_overlap"</span><span data-if="com" style="display:none">"detection_tiling_overlap"</span><span data-if="dotnet" style="display:none">"detection_tiling_overlap"</span><span data-if="python" style="display:none">"detection_tiling_overlap"</span>, <span data-if="hdevelop" style="display:inline">'recognition_alphabet'</span><span data-if="c" style="display:none">"recognition_alphabet"</span><span data-if="cpp" style="display:none">"recognition_alphabet"</span><span data-if="com" style="display:none">"recognition_alphabet"</span><span data-if="dotnet" style="display:none">"recognition_alphabet"</span><span data-if="python" style="display:none">"recognition_alphabet"</span>, <span data-if="hdevelop" style="display:inline">'recognition_alphabet_internal'</span><span data-if="c" style="display:none">"recognition_alphabet_internal"</span><span data-if="cpp" style="display:none">"recognition_alphabet_internal"</span><span data-if="com" style="display:none">"recognition_alphabet_internal"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_internal"</span><span data-if="python" style="display:none">"recognition_alphabet_internal"</span>, <span data-if="hdevelop" style="display:inline">'recognition_alphabet_mapping'</span><span data-if="c" style="display:none">"recognition_alphabet_mapping"</span><span data-if="cpp" style="display:none">"recognition_alphabet_mapping"</span><span data-if="com" style="display:none">"recognition_alphabet_mapping"</span><span data-if="dotnet" style="display:none">"recognition_alphabet_mapping"</span><span data-if="python" style="display:none">"recognition_alphabet_mapping"</span>, <span data-if="hdevelop" style="display:inline">'recognition_batch_size'</span><span data-if="c" style="display:none">"recognition_batch_size"</span><span data-if="cpp" style="display:none">"recognition_batch_size"</span><span data-if="com" style="display:none">"recognition_batch_size"</span><span data-if="dotnet" style="display:none">"recognition_batch_size"</span><span data-if="python" style="display:none">"recognition_batch_size"</span>, <span data-if="hdevelop" style="display:inline">'recognition_device'</span><span data-if="c" style="display:none">"recognition_device"</span><span data-if="cpp" style="display:none">"recognition_device"</span><span data-if="com" style="display:none">"recognition_device"</span><span data-if="dotnet" style="display:none">"recognition_device"</span><span data-if="python" style="display:none">"recognition_device"</span>, <span data-if="hdevelop" style="display:inline">'recognition_image_dimensions'</span><span data-if="c" style="display:none">"recognition_image_dimensions"</span><span data-if="cpp" style="display:none">"recognition_image_dimensions"</span><span data-if="com" style="display:none">"recognition_image_dimensions"</span><span data-if="dotnet" style="display:none">"recognition_image_dimensions"</span><span data-if="python" style="display:none">"recognition_image_dimensions"</span>, <span data-if="hdevelop" style="display:inline">'recognition_image_height'</span><span data-if="c" style="display:none">"recognition_image_height"</span><span data-if="cpp" style="display:none">"recognition_image_height"</span><span data-if="com" style="display:none">"recognition_image_height"</span><span data-if="dotnet" style="display:none">"recognition_image_height"</span><span data-if="python" style="display:none">"recognition_image_height"</span>, <span data-if="hdevelop" style="display:inline">'recognition_image_width'</span><span data-if="c" style="display:none">"recognition_image_width"</span><span data-if="cpp" style="display:none">"recognition_image_width"</span><span data-if="com" style="display:none">"recognition_image_width"</span><span data-if="dotnet" style="display:none">"recognition_image_width"</span><span data-if="python" style="display:none">"recognition_image_width"</span>, <span data-if="hdevelop" style="display:inline">'recognition_model'</span><span data-if="c" style="display:none">"recognition_model"</span><span data-if="cpp" style="display:none">"recognition_model"</span><span data-if="com" style="display:none">"recognition_model"</span><span data-if="dotnet" style="display:none">"recognition_model"</span><span data-if="python" style="display:none">"recognition_model"</span>, <span data-if="hdevelop" style="display:inline">'recognition_num_char_candidates'</span><span data-if="c" style="display:none">"recognition_num_char_candidates"</span><span data-if="cpp" style="display:none">"recognition_num_char_candidates"</span><span data-if="com" style="display:none">"recognition_num_char_candidates"</span><span data-if="dotnet" style="display:none">"recognition_num_char_candidates"</span><span data-if="python" style="display:none">"recognition_num_char_candidates"</span></p>
</div>
  <div class="par">
<div class="parhead">
<span id="GenParamValue" class="parname"><b><code><span data-if="hdevelop" style="display:inline">GenParamValue</span><span data-if="c" style="display:none">GenParamValue</span><span data-if="cpp" style="display:none">GenParamValue</span><span data-if="com" style="display:none">GenParamValue</span><span data-if="dotnet" style="display:none">genParamValue</span><span data-if="python" style="display:none">gen_param_value</span></code></b> (output_control)  </span><span>attribute.value(-array) <code>→</code> <span data-if="dotnet" style="display:none"><a href="HTuple.html">HTuple</a></span><span data-if="python" style="display:none">Sequence[HTupleElementType]</span><span data-if="cpp" style="display:none"><a href="HTuple.html">HTuple</a></span><span data-if="c" style="display:none">Htuple</span><span data-if="hdevelop" style="display:inline"> (integer / </span><span data-if="hdevelop" style="display:inline">handle / </span><span data-if="hdevelop" style="display:inline">string / </span><span data-if="hdevelop" style="display:inline">real)</span><span data-if="dotnet" style="display:none"> (<i>int</i> / </span><span data-if="dotnet" style="display:none">long / </span><span data-if="dotnet" style="display:none">HHandle / </span><span data-if="dotnet" style="display:none">string / </span><span data-if="dotnet" style="display:none">double)</span><span data-if="cpp" style="display:none"> (<i>Hlong</i> / </span><span data-if="cpp" style="display:none">HHandle / </span><span data-if="cpp" style="display:none">HString / </span><span data-if="cpp" style="display:none">double)</span><span data-if="c" style="display:none"> (<i>Hlong</i> / </span><span data-if="c" style="display:none">handle / </span><span data-if="c" style="display:none">char* / </span><span data-if="c" style="display:none">double)</span></span>
</div>
<p class="pardesc">Value of the generic parameter.</p>
</div>
<h2 id="sec_result">结果</h2>
<p>如果参数均有效，算子 <code><span data-if="hdevelop" style="display:inline">get_deep_ocr_param</span><span data-if="c" style="display:none">get_deep_ocr_param</span><span data-if="cpp" style="display:none">GetDeepOcrParam</span><span data-if="com" style="display:none">GetDeepOcrParam</span><span data-if="dotnet" style="display:none">GetDeepOcrParam</span><span data-if="python" style="display:none">get_deep_ocr_param</span></code>
返回值 <TT>2</TT> (
      <TT>H_MSG_TRUE</TT>)
    .  如有必要，将引发异常。</p>
<h2 id="sec_predecessors">可能的前置算子</h2>
<p>
<code><a href="create_deep_ocr.html"><span data-if="hdevelop" style="display:inline">create_deep_ocr</span><span data-if="c" style="display:none">create_deep_ocr</span><span data-if="cpp" style="display:none">CreateDeepOcr</span><span data-if="com" style="display:none">CreateDeepOcr</span><span data-if="dotnet" style="display:none">CreateDeepOcr</span><span data-if="python" style="display:none">create_deep_ocr</span></a></code>, 
<code><a href="set_deep_ocr_param.html"><span data-if="hdevelop" style="display:inline">set_deep_ocr_param</span><span data-if="c" style="display:none">set_deep_ocr_param</span><span data-if="cpp" style="display:none">SetDeepOcrParam</span><span data-if="com" style="display:none">SetDeepOcrParam</span><span data-if="dotnet" style="display:none">SetDeepOcrParam</span><span data-if="python" style="display:none">set_deep_ocr_param</span></a></code>
</p>
<h2 id="sec_successors">可能的后置算子</h2>
<p>
<code><a href="set_deep_ocr_param.html"><span data-if="hdevelop" style="display:inline">set_deep_ocr_param</span><span data-if="c" style="display:none">set_deep_ocr_param</span><span data-if="cpp" style="display:none">SetDeepOcrParam</span><span data-if="com" style="display:none">SetDeepOcrParam</span><span data-if="dotnet" style="display:none">SetDeepOcrParam</span><span data-if="python" style="display:none">set_deep_ocr_param</span></a></code>, 
<code><a href="apply_deep_ocr.html"><span data-if="hdevelop" style="display:inline">apply_deep_ocr</span><span data-if="c" style="display:none">apply_deep_ocr</span><span data-if="cpp" style="display:none">ApplyDeepOcr</span><span data-if="com" style="display:none">ApplyDeepOcr</span><span data-if="dotnet" style="display:none">ApplyDeepOcr</span><span data-if="python" style="display:none">apply_deep_ocr</span></a></code>
</p>
<h2 id="sec_see">参考其它</h2>
<p>
<code><a href="set_deep_ocr_param.html"><span data-if="hdevelop" style="display:inline">set_deep_ocr_param</span><span data-if="c" style="display:none">set_deep_ocr_param</span><span data-if="cpp" style="display:none">SetDeepOcrParam</span><span data-if="com" style="display:none">SetDeepOcrParam</span><span data-if="dotnet" style="display:none">SetDeepOcrParam</span><span data-if="python" style="display:none">set_deep_ocr_param</span></a></code>
</p>
<h2 id="sec_module">模块</h2>
<p>
OCR/OCV</p>
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